During architectural conception phase,building maintenance problematic is mostly a result of the unintentional use of preconceived architectonical solutions rather than a consequence of a specific influence of mainten...During architectural conception phase,building maintenance problematic is mostly a result of the unintentional use of preconceived architectonical solutions rather than a consequence of a specific influence of maintenance requirements.Hardly the architect in the act of design understands the importance of these solutions in the service life span of a building.Being aware of this,is it possible for the architect to be supplied with a decision support system that allows him to consider the implications of building maintenance since the early design phases? Having awareness of this problem and its consequences in the early design phases a research project was started at the Faculty Engineering of the University of Oporto(FEUP),under which the implications of building maintenance in the act of architectural design is studied.This article presents the methodology developed to identify the needs of maintenance of buildings based on a DSS-decision support system that provides simple tools the architect can use in design phase.This methodology is based on decomposition of building parts-Elements Source of Maintenance ESM-,and subsequently,a set of functional requirements that determine the performance regarding building maintenance on account of architectural decisions.Relevant maintenance actions are defined: Inspection,Pro-action,Cleaning,Correction,Replacement,Legal enforcement,Limits of use.One can thus set up a relationship between the act of design and its performance framework based on behavior,intervention and the ownership of the work of architecture.Using a Multicriteria Analysis(MCA) a qualitative evaluation of different options based on maintenance requirements accomplishment.Conclusions on the importance of architectural conception concerning the building maintenance were clearly arrived at and the utility of the developed decision support tool was also highlighted.展开更多
Optimization of architecture design has recently drawn research interest. System deployment optimization （SDO） refers to the process of optimizing systems that are being deployed to activi- ties. This paper first fo...Optimization of architecture design has recently drawn research interest. System deployment optimization （SDO） refers to the process of optimizing systems that are being deployed to activi- ties. This paper first formulates a mathematical model to theorize and operationalize the SDO problem and then identifies optimal so- lutions to solve the SDO problem. In the solutions, the success rate of the combat task is maximized, whereas the execution time of the task and the cost of changes in the system structure are mini- mized. The presented optimized algorithm generates an optimal solution without the need to check the entire search space. A novel method is finally proposed based on the combination of heuristic method and genetic algorithm （HGA）, as well as the combination of heuristic method and particle swarm optimization （HPSO）. Experi- ment results show that the HPSO method generates solutions faster than particle swarm optimization （PSO） and genetic algo- rithm （GA） in terms of execution time and performs more efficiently than the heuristic method in terms of determining the best solution.展开更多
文摘During architectural conception phase,building maintenance problematic is mostly a result of the unintentional use of preconceived architectonical solutions rather than a consequence of a specific influence of maintenance requirements.Hardly the architect in the act of design understands the importance of these solutions in the service life span of a building.Being aware of this,is it possible for the architect to be supplied with a decision support system that allows him to consider the implications of building maintenance since the early design phases? Having awareness of this problem and its consequences in the early design phases a research project was started at the Faculty Engineering of the University of Oporto(FEUP),under which the implications of building maintenance in the act of architectural design is studied.This article presents the methodology developed to identify the needs of maintenance of buildings based on a DSS-decision support system that provides simple tools the architect can use in design phase.This methodology is based on decomposition of building parts-Elements Source of Maintenance ESM-,and subsequently,a set of functional requirements that determine the performance regarding building maintenance on account of architectural decisions.Relevant maintenance actions are defined: Inspection,Pro-action,Cleaning,Correction,Replacement,Legal enforcement,Limits of use.One can thus set up a relationship between the act of design and its performance framework based on behavior,intervention and the ownership of the work of architecture.Using a Multicriteria Analysis(MCA) a qualitative evaluation of different options based on maintenance requirements accomplishment.Conclusions on the importance of architectural conception concerning the building maintenance were clearly arrived at and the utility of the developed decision support tool was also highlighted.
基金supported by the National Natural Science Foundation of China(71171197)the National Basic Research Program of China(973 Program)(613154)
文摘Optimization of architecture design has recently drawn research interest. System deployment optimization （SDO） refers to the process of optimizing systems that are being deployed to activi- ties. This paper first formulates a mathematical model to theorize and operationalize the SDO problem and then identifies optimal so- lutions to solve the SDO problem. In the solutions, the success rate of the combat task is maximized, whereas the execution time of the task and the cost of changes in the system structure are mini- mized. The presented optimized algorithm generates an optimal solution without the need to check the entire search space. A novel method is finally proposed based on the combination of heuristic method and genetic algorithm （HGA）, as well as the combination of heuristic method and particle swarm optimization （HPSO）. Experi- ment results show that the HPSO method generates solutions faster than particle swarm optimization （PSO） and genetic algo- rithm （GA） in terms of execution time and performs more efficiently than the heuristic method in terms of determining the best solution.
